Velocity control in a right-turn across traffic scenario for autonomous vehicles using kernel-based reinforcement learning

Recently, advanced control methods like machine leaning are increasingly applied to autonomous vehicle. This paper focuses on velocity control in a right-turn traffic scenario. A Markov Decision Processes(MDPs) is modeled and the actor-critic reinforcement learning architecture is employed. Then the...

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Vydáno v:2017 Chinese Automation Congress (CAC) s. 6211 - 6216
Hlavní autoři: Yuxiang Zhang, Bingzhao Gao, Lulu Guo, Hong Chen, Jinghua Zhao
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2017
Témata:
autonomous vehicle
kernel-based least squares policy iteration (KLSPI)
reinforcement learning (RL)
Systems modeling
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Abstract Recently, advanced control methods like machine leaning are increasingly applied to autonomous vehicle. This paper focuses on velocity control in a right-turn traffic scenario. A Markov Decision Processes(MDPs) is modeled and the actor-critic reinforcement learning architecture is employed. Then the kernel-based least squares policy iteration algorithm(KLSPI) is applied. Simulation results show that the proposed method can perform different policy in different cases, which preliminarily verify the rationality.
AbstractList Recently, advanced control methods like machine leaning are increasingly applied to autonomous vehicle. This paper focuses on velocity control in a right-turn traffic scenario. A Markov Decision Processes(MDPs) is modeled and the actor-critic reinforcement learning architecture is employed. Then the kernel-based least squares policy iteration algorithm(KLSPI) is applied. Simulation results show that the proposed method can perform different policy in different cases, which preliminarily verify the rationality.
Author Yuxiang Zhang
Bingzhao Gao
Hong Chen
Jinghua Zhao
Lulu Guo
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  surname: Bingzhao Gao
  fullname: Bingzhao Gao
  organization: State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
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  surname: Lulu Guo
  fullname: Lulu Guo
  organization: State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
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  surname: Hong Chen
  fullname: Hong Chen
  email: chenh@jlu.edu.cn
  organization: State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
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  surname: Jinghua Zhao
  fullname: Jinghua Zhao
  organization: Comput. Coll., Jilin Normal Univ., Siping, China
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Snippet Recently, advanced control methods like machine leaning are increasingly applied to autonomous vehicle. This paper focuses on velocity control in a right-turn...
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StartPage 6211
SubjectTerms autonomous vehicle
kernel-based least squares policy iteration (KLSPI)
reinforcement learning (RL)
Systems modeling
Title Velocity control in a right-turn across traffic scenario for autonomous vehicles using kernel-based reinforcement learning
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